ABSTRACT AND PROJECT SUMMARY Understanding the fundamental mechanisms that drive cellular processes within the complexity of biological systems remains a formidable task. Addressing this challenge requires the development of new technologies that not only increase the number of analytes that can be measured in a single experiment, but also link measurements across multiple parameters to reveal insights into mechanism. Here, I build upon a spectral encoding platform we have recently developed to create two such technologies that will dramatically boost the information content of high-throughput measurements by increasing their dimensionality. First, I will combine tools from microfluidics, electrical engineering, and chemistry to enable code-directed synthesis of programmable peptide libraries directly on spectrally encoded beads. By using the code embedded within each bead to direct the chemical synthesis of a specific peptide on its surface, this scheme simultaneously increases potential library size while dramatically lowering synthesis costs. In addition, peptides of interest in downstream assays can be identified via imaging alone, increasing ease of readout. As a first biological application, I will create libraries to probe proteolytic signatures that correlate with disease, with the goal of identifying peptide sequences that can be used in the future as diagnostic and imaging probes. In future applications, these programmable, proteome-scale libraries would facilitate a wide range of additional applications that include enzyme-substrate profiling (e.g. kinases, phosphatases, proteases), immune repertoire profiling, and protein-protein interaction screening. Second, I will probe both the causes and effects of cellular heterogeneity by developing a new assay that enables the measurement of both transcriptome and phenotype for many single cells in parallel. Here, spectrally encoded beads with unique oligonucleotide barcodes conjugated to their surface provide the critical link, allowing sequencing reads measuring transcript levels to be traced back not only to a single cell, but to a particular single cell that has already been characterized phenotypically. As a proof of principle, I will use the assay to measure levels of 40 secreted proteins and hundreds of transcripts for > 1000 cells, with the goal of understanding whether functional diversity in secreted protein profiles is transcriptionally encoded. In future work, this same scheme could be used to probe the molecular drivers of heterogeneity for a wide number of additional phenotypes, including intracellular and secreted protein levels, motility, cytotoxicity, morphology, and proliferation. Such assays would have tremendous biological and translational applications, from understanding how genetically identical immune cells clonally expand to yield diverse functional phenotypes to investigating the mechanisms that drive stem cell differentiation.